The point of going to school is to learn all the details of what goes into making things, so when you actually make a thing, you understand how it’s supposed to come together, including important details like correct design that can support the goal, etc. That’s the “getting stronger” part that you can’t skip if you expect to be successful. Only after you’ve done the work and understand the details can you be successful using the power tools to make things.

>Here's the thing -- I don't care about "getting stronger."

Let's not mince words here, what you mean is that you don't care to learn about a craft. You just want to get to the end result, and you are using the shiny new tool that promises to take you from 0 to 100% with little to no effort.

In this way, I'd argue what you are doing is not "creating", but engaging in a new form of consumption. It used to be you relied on algorithms to present to you content that you found fun, but the problem was that algorithm required other humans to create that content for you to later consume. Now with LLMs, you remove the other humans from the loop, and you can prompt the AI directly with exactly what you wish to see in that moment, down to the fine grained details of the thing, and after enough prompts, the AI gives you something that might be what you asked for.

You are rotting your brain.

> to stretch the analogy, I don't believe much is lost "intellectually" by my use of a mech suit, as long as I observe carefully.

With all respect, that's nonsense.

Absolutely no one gains more than a superficial grasp of a skill just by observing.

And even with a good grasp of skills, human boredom is going to atrophy any ability you have to intervene.

It's why the SDCs (Tesla, I think) that required the driver to stay alert to take control while the car drove itself were such a danger - after 20+ hours of not having to to anything, the very first time a normal reaction time to an emergency is required, the driver is too slow to take over.

If you think you are learning something reviewing the LLM agent's output, try this: choose a new project in a language and framework you have never used, do your usual workflow of reviewing the LLMs PRs, and then the next day try to do a simple project in that new language and framework (that's the test of how much you learned).

Compare that result to doing a small project in a new language, and then the next day doing a different small project in that same language.

If you're at all honest with yourself, or care whether you atrophy or not, you'd actually run that experiment and control and objectively judge the results.

> Everyone knows that debugging is twice as hard as writing a program in the first place. So if you're as clever as you can be when you write it, how will you ever debug it? — The Elements of Programming Style, 2nd edition, chapter 2

If you weren't even "clever enough" to write the program yourself (or, more precisely, if you never cultivated a sufficiently deep knowledge of the tools & domain you were working with), how do you expect to fix it when things go wrong? Chatbots can do a lot, but they're ultimately just bots, and they get stuck & give up in ways that professionals cannot afford to. You do still need to develop domain knowledge and "get stronger" to keep pace with your product.

Big codebases decay and become difficult to work with very easily. In the hands-off vibe-coded projects I've seen, that rate of decay was extremely accelerated. I think it will prove easy for people to get over their skis with coding agents in the long run.

This analogy works pretty well. Too much time doing everything in it and your muscles will atrophy. Some edge cases will be better if you jump out and use your hands.

OK, it’s a mech suit. The question under discussion is, do you need to learn to walk first, before you climb into it? My life experience has shown me you can’t learn things by “observing”, only by doing.

If observing was as good as doing, experience would mean nothing.

Thinking through the issue, instead of having the solve presented to you, is the part where you exercise your mental muscles. A good parallel is martial arts.

You can watch it all you want, but you'll never be skilled unless you actually do it.

If all I know is the mech suit, I’ll struggle with tasks that I can’t use it for. Maybe even get stuck completely. Now it’s a skill issue because I never got my 10k hours in and I don’t even know what to observe or how to explain the outcome I want.

In true HN fashion of trading analogies, it’s like starting out full powered in a game and then having it all taken away after the tutorial. You get full powered again at the end but not after being challenged along the way.

This makes the mech suit attractive to newcomers and non-programmers, but only because they see product in massively simplified terms. Because they don’t know what they don’t know.

The mech suit works well until you need to maintain stateful systems. I've found that while initial output is faster, the AI tends to introduce subtle concurrency bugs between Redis and Postgres that are a nightmare to debug later. You get the speed up front but end up paying for it with a fragile architecture.

> "it's not an autonomous robot, it's a mech suit."

Or "An [electric] bicycle for the mind." Steve Jobs/simonw

No, it's not a mech suit. A mech suit doesn't fire its canister rifle at friendly units and then say "You're absolutely right! I should have done an IFF before attacking that unit." (And if it did the engineer responsible should be drawn and quartered.) Mech-suit programming AI would look like something that reads your brainwaves and transduces them into text, letting you think your code into the machine. I'd totally use that if I had it.

> I want to make things

You need to be strong to do so. Things of any quality or value at least.